Tag Archive for President Obama

My latest video is from a talk I gave back in July at the RightOnline conference. I had 5 minutes to give a talk and I had something all planned out… until President Obama gave this speech in Cleveland. In this speech he stated:

Our businesses have gone back to basics and created over 4 million jobs in the last 27 months — (applause) — more private sector jobs than were created during the entire seven years before this crisis — in a little over two years

I decided to check him on his jobs claims and I summarized my findings in my talk, which I reproduced for this video.

There is a more comprehensive jobs number (employment) that tells a very different story.

Deception Through Selection

And here is where I give a little more detail on what numbers I used. First a little background:

President Obama gave this speech on June 14, 2012, so at that time we were using the most recent BLS jobs report which had number up to May. Counting backward from there, that means Obama was counting from March 2010 to May 2012.

March 2010 – 106,914,000 private sector payrolls

May 2012 – 111,040,000 private sector payrolls (revised up 32,000 in later reports to 111,072,000)

I was assuming that when Obama said “before the crisis” he meant before we started losing jobs. That would put the “7 year” number from February 2001 to February 2008.

February 2001 – 111,623,000 private sector payrolls

February 2008 – 115,511,000 private sector payrolls

Difference in 7 years – 3.88 million private sector payrolls

As you can see, the Obama graph is a nice simply upward slope including only the part of his presidency where he gained jobs. In fact, he starts counting only after the jobs number completely bottomed out. If we look at the jobs record during his entire time in office, we get this chart

Is there any thing wrong with not counting those initial job losses? I don’t think so. I think it is a perfectly reasonable thing to do to say “let’s look at the strength of the recovery alone” and use that metric to count. But it is incredibly disingenuous of the Obama team to completely discount job losses for themselves but then turn around and count them in the comparison data point.

In the video, I point out that using “6 years before the crisis” or “5 years before the crisis” result in vastly larger numbers (6.4 million and 7.1 million respectively), but what I’m really interested in here (and what I’d like to expand upon) is comparing private sector payroll growth that Obama is touting to the private sector payroll growth under Bush.

I looked at this a couple months ago and was a little shocked to see the following chart, but here it is. Starting at the low point of private sector jobs growth, if we chart what I will (for simplicity sake) call the Bush recovery (starting in July 2003) and the Obama recovery (starting in March 2009) using the latest data, we get:

As you can see… the weird thing about this current recovery is how closely it is tracking to the previous recovery in terms of private payroll increases. For Obama to pretend he is substantially better than Bush on this metric is nothing short of fantasy.

The Larger Jobs Number (Employment)

The first one is the establishment data (B Tables) and this is a survey counts jobs by industry. Think of it as someone calling a bunch of businesses and asking “How many people do you have on payroll?” They directly sample over 100,000 businesses and it has a margin of error of about 100K jobs.

The second one is household data (A Tables) and this is a survey of households. Think of it as someone calling a bunch of people and asking “Do you have a job?” It samples about 60,000 households and has a much larger margin of error (400K jobs).

The establishment data is usually used for month-to-month job counts in part because it tends to be a much less volatile metric (household data can swing somewhat wildly). That’s why, when you hear about “X jobs gained last month”, they use the number from the establishment survey.

However, a weird thing happened in the 00’s with the household survey. If we take the private payrolls and compare them to what I’m going to call “private employment” (the A table employment number minus government jobs), we see a massive difference in the job count.

That’s a 3 million job difference between private payrolls and private employment. This is way outside the margin of error. Something happened there, althoughI’m not sure what. Maybe self-employment increased, or people made ends meet w/ irregular non-payroll income or farm employment jumped. I honestly don’t know and anything I say here is pure speculation. But there it is, clear as day.

This is why Obama focuses so much on private payrolls as the metric he uses. Most fact-check organizations are not savvy enough to notice that there is this huge discrepancy in the jobs data from survey to survey. They only think to check Obama’s statements against the private payrolls data, not the overall employment.

As you can see, the change in both jobs numbers are nearly identical. If we add in government job losses, we actually get a negative number on employment change since his inauguration. This shows that something was happening in the last recovery that isn’t happening in this one.

Back in 2009 I made a visualization about the deficits we were expecting under President Barack Obama. I called it the “National Debt Road Trip” and it was moderately popular.

Today, after nearly 3 years, I have updated it with a new video:

The video itself is just an overview of data that I’ve been toying around with for a month or so. I’ll do an in depth look at the data first and then answer some questions close observers might have about the data.

For the presidents where I had daily debt data (from 1993 – present), I used “inauguration-to-inauguration” debt numbers.

When I didn’t have those (for Ronald Reagan & George H W Bush) I used the yearly debt numbers including the fiscal year for which they were responsible. So for Reagan I used October 1981-October 1989 and for HW Bush I used October 1989 to Jan 20, 1993 (when daily data became available).

With all this information, I came up w/ the following data points (adjusted for inflation)

What I Assume Will Be Frequently Asked Questions

Q: Why are your numbers different here than they were in your original video?

A: Back in 2009, I was new to researching federal financial data. I used a different, less accurate method of inflation calculation for my first video. Additionally, the inflation data of the last 3 years ended up altering where George W. Bush “stopped” in debt accrual. Finally, I tried to be all fancy in my calculations last time, making estimations to calculate debt between fiscal years. I didn’t do that this time so, while the numbers are in the same ballpark as the first video, I believe them to be a more accurate representation.

Q: You said “during the first 38 months of his presidency” but you crossed out 39 months. Why?

A: Good eye. At that point in the video I was disregarding debt accrued from January 20, 2009 to March 21, 2012. That is almost exactly a 38 month period, but I crossed out two partial months (January 2009 and March 2012) for the sake of simplicity.

Q: Why use “inauguration-to-inauguration” data instead of “fiscal-year-to-fiscal-year”? In short, why did you assign President Obama the debt from 2009? That was a budget Bush signed, he should be blamed for the debt.

A: Normally, I would agree on this count. However, President Obama’s stimulus deeply complicates the matter. Federal spending for 2009 was drastically higher than the budget that was passed due to the Obama stimulus. Add to that the sizable tax credits from the stimulus and we see President Obama’s policies have significant effect on both the revenue and the spending side. I felt that doing calculations based on assumptions of what could have happened would be presumptuous and call the data into question. So instead I tried to use numbers that could be easily fact-checked.

Q: I have a chart here that *proves* George W. Bush is responsible for all this debt. Why do you hate the truth?

A: That’s less of a question and more of a pout, but here is my position: I’ve seen that chart and I’m of two minds about it. On the one hand, yes, Bush implemented a lot of policies that racked up a lot of debt. On the other hand, Obama has been in office an awful long time to not be held accountable for the state of federal finances. That is why I separated out “before” and “after” into two different speeds.

I think it is a totally valid question to ask “Now that the economy has turned around why haven’t federal finances?” Is Barack Obama the only president in the history of ever to not be held responsible for anything that happened during his presidency? It seems rather insulting to President Obama to imply he is so ineffectual that, even after 3+ years in office, he is merely a figurehead doll swept along the current of a river he cannot control. (Worst. Metaphor. Ever.)

Q: Why didn’t you use debt as a % of GDP?

A: A couple reasons. The first is that doing so really complicates the metaphor I’m using. Secondly, it would actually put President Obama at a disadvantage because debt as a % of GDP spiked drastically in his first year since not only did the debt increase, but the GDP decreased increasing the number from the numerator and the denominator side of the ratio. Thirdly, while the president doesn’t have total control over the deficit, he has far more control over it than over GDP increases or decreases. Using “debt as a % of GDP” is a less direct measurement of presidential responsibility.

Q: What do you mean by “optimistic revenue estimates”?

A: According to President Obama’s own budget, he expects 2014 revenue to be 43% higher than 2011 revenue. The only time in modern fiscal history that this has happened was when inflation was in the double digits, so the increase in revenue wasn’t a real increase. He’s already way off target for his 2012 revenue estimates, so I don’t think it’s a stretch to say these are “optimistic revenue estimates”.

In my video I wanted to give President Obama the benefit of the doubt. I wanted to say “Even though I think you’re being overly optimistic, we will use your numbers as an act of good faith.” The horrifying thing is that, even with President Obama’s extreme optimism on the revenue side of the equation, he still projects monster deficits long into the future.

The big point here is that President Obama has no plan to deal with deficits or debt. He’s kinda-sorta hoping that we’ll start making enough revenue to catch up to the spending increases, but he kinda-sorta knows that isn’t going to happen. Yet he has made no moves to reduce spending to match (or even come within screaming distance of) federal revenues.

This is a companion piece to the previous post, so please read both of them. Here I’m going to lay out the script I had written for debunking the chart I created that asked the question “Does a Republican Congress Create More Jobs?” and then implied with a chart that this was indeed the case. I’ll walk through some process for creating charts and then talk about why I would create a chart that I was just going to debunk.

How to Make Number Say Anything You Want

Do you want to convince people that your side is right with only the flimsiest proof? Does the idea of tricking people with numbers make you all happy inside? Then come join us as we walk through “How To Use Charts To Say Anything”

Step 1: Massaging the Data

The first step is to grab the data that makes your point the best. Let’s use it to prove that a Democratic Congress is bad for jobs.

“How can we do such a thing” you ask?

In the first case, the raw jobs data looks like this

but the final chart looks like this.

How did they do that? Was it magic?

Nope, we simply smoothed the data. The raw data is a little too chaotic and has too many data point to tell the straightforward story that we want. So instead, we’ll average the monthly data so that we have quarterly data. There… now we have some nice smooth straightforward data

Step 2: Pick colors that make you look good

Next, we pick some colors. Let’s make the Democrats blue dark and bold, give it a bit of an angry feel to it. This is our way of getting the audience to look at the democrats in a harsh way. We could try to soften up on the Republicans more, but too soft of a red would look pink and we don’t want that.

Let’s compare our colors to the Excel defaults:

Step 3: Do NOT give any context!

Finally, and this is the most important part, only give information that is helpful.

Let everyone know that we saw 8 million jobs added to the economy while the Republicans were in charge and make a point to show that we lost 8 million jobs while the Democrats were in charge. But don’t mention that the Republicans took Congress only a year after 9/11 at a time when the job market was particularly low. Otherwise people will think it’s a “Well, they can’t fall off the floor” thing.

And make sure you don’t mention anything about the real estate market and how the bubble drove the labor market in a way that was clearly unsustainable. We don’t want the viewers to be confused with all these relevant details. We want them to say “Republicans good, Democrats bad”.

<End Script>

Everyone here was incredibly kind to put up with my bullshit chart for as long as I left it up without explanation. I’d like to say unequivocally: My chart is propaganda… just like the Obama administration’s chart. I was trying to use my chart as a visual talking point that said:

If you have no ethical qualms, data visualizations can be manipulated to say exactly what you want them to say.

My chart implies that the Republicans were responsible for the jobs growth between 2003 and 2007 and that Democrats were responsible for the drastic decline from 2007 to the present. Let me state plainly, I do not think that is the case.

But if we just play around with the data the right way, we get what seems to be a clear picture that portrays a correlation and gets on its hands and knees and begs us to draw causation from it. Most people will do exactly that.

I can spend hours walking patiently through what is wrong with the Obama administration’s chart. Let me recap the high points here:

If you look at the data with the context of what President Obama’s team was hoping the stimulus would do, the power of the chart disappears.

If you look at the data with the understanding that they’re charting a first derivative, you realize that we haven’t gained jobs, we’re just losing them more slowly and the power of the chart disappears.

If you look at the data with the understanding that they didn’t even start spending the stimulus until the job loss had started slowing down, the power of the chart disappears.

If you look at the data in the context of other recessions, you’ll realize that, far from showing a drastic improvement, the numbers represent a devastatingly slow jobs recovery compared to other recoveries and the power of the chart disappears.

But this kind of explanatory rebuttal would interest those already convinced. The chart I made had a power that an calm explanatory video wouldn’t have. Quite frankly, I hate that this is the case. Like President Obama’s chart, my chart doesn’t teach people anything about economics or lead people to learn important things about unemployment.

The only valuable thing my chart teaches is that charts can portray accurate data and still be manipulated to coach people along to poor conclusions. The only reason I even put my chart up is because it is the graphical equivalent of drawing out the Obama administration’s argument to its logical conclusion. My chart works with the same data, the same assumptions, and the same implications. And it leads to a completely different conclusion.

My point here is that it isn’t brilliant. It’s juvenile. It’s the chart equivalent of a crass political cartoon with a Snidely Whiplash mustache drawn on the bad guys. It’s a design trick imagined by cynical, self-congratulatory children fresh out of graduate school who pat themselves on the back for their ability to fool people who they think are too stupid to know the difference. They think they are special because they can get powerful people to flatter them for their ability to lie.

But they aren’t special. I can play that same childish game in my free time. The difference if that I want people to know that it’s a trick. They would rather see people fooled.

I’ve been trying to find the time to make a video for this, but the fact of the matter is that I’m simply too slammed with all my work (I have a huge conference in two days). And I’m really kind of sick of my chart that I put up with basically no explanation. I basically created my chart as a rebuttal to this chart put out by the Obama administration. In this post, I debunk the Obama chart. In the next one, I debunk my own.

I’m basically just going to dump the script that I had written. Imagine my voice with some happy visuals that I don’t have time to make. I’ll add some additional comments at the end. Imagine a sing-song snake-oil salesman. That was what I was going for.

<Start Script>

How To Use Charts To Say Anything

Do you want to convince people that your side is right with only the flimsiest proof? Does the idea of tricking people with numbers make you all happy inside? Then come join us as we walk through “How To Use Charts To Say Anything”.

Step 1: Massaging the Data

The first step is to grab the data that makes your point the best. Let’s use it to prove that a Democratic president is good for jobs.

“How can we do such a thing” you ask?

Let’s grab some raw jobs data. We’re going to take this data

and make it look like this:

How did we do that? Was it magic?

Nope, it’s called the first derivative. It works like this. Instead of worrying about how high the line is, we’re only going to worry about how steep the line is. That way, the number will look good even if we keep losing jobs. Instead of charting how many jobs there are, we’re charting how many jobs we’re still losing.

That turns the first chart (which looks bad) into the second chart (which looks good).

Step 2: Pick colors that make you look good

Next, we pick some colors. We could pick the default colors that Excel gives us when we chart two different kinds of numbers. But that’s too neutral. By way of comparison:

As you can see, we’ve taken the default red (for George Bush) and made it darker and richer. This is like drawing a Snidely Whiplash mustache on him so that we know he’s the bad guy. Then, we’ll make the President Obama blue lighter and softer so we know he’s the good guy.

Step 3: Do NOT give any context!

Finally, and this is the most important part, only give information that is helpful. And by helpful, I mean favorable to your side.

It’s OK to mention that President Obama signed the stimulus bill into law in the first quarter of 2009.

It’s not OK to mention that the initial stimulus reports from the first and second quarter were totally blank, which means that they didn’t really start spending the money until July.

Also, you should forget to mention that as of December, we’ve only spent 10% of the stimulus money.

If you give all of this unhelpful information, people might draw the conclusion that the stimulus didn’t really help very much.

And that would be bad.

Remember, we’re not interested in helping people understand the complexities of the economy. We just want them to look at the chart and say, “Bush bad. Obama good.”

<End Script>

I got my numbers for the last part of this from the stimulus reports on recovery.gov. Since I started looking at the data back in late 2009, they’ve changed the way they organize the data. Until a little over a month ago, the reports for 2009, Q1 and 2009, Q2 were blank. Zero data. Nothing. In the 2009 Q3 data they reported giving out about 4% of the stimulus money. By the end of 2009 Q4, they had reported giving out 10% of the simulus money.

Since then, they took the empty Q1, Q2 and the actual Q3 data and relabeled the file so that the Q3 data now says “February 17 – September 30, 2009″. There is no way to tell for certain when the money was sent out, but the amount of money marked as “recieved” ran on a curve that was about 4 months off. (Example: Most of the money that was marked as “recieved” was applied for in March, April and May. Very few places that applied for money after May marked it as recieved by the end of September. So…we see job losses slowing even before the money was making it out the door.

OK. Now to talk about my rebuttal chart and a well deserved explanation. I have the greatest readers of all time and many of you have pointed out that my rebuttal chart (seen here) commits many of the same fallacies that the Obama chart has.

My response to that would be “Yes it does. It was meant to.” I created that chart as the visual equivalent of saying “If your logic is correct, than you would be forced to accept this other conclusion as well since it uses the same logic.”

Both charts use jobs data taken from the same place, displayed the same way, stripped of context and used to push an ideological point using an implicit “correlation mean causation” line of argumentation.

Let me be clear: I do not think that a Republican Congress is the driving factor behind 8 million jobs created and I would NEVER say that. But I would say “Your chart implies that Obama is responsible for the slowing of job loss. If that is your argument, I would like to use the same chart logic to say that we need a Republican Congress to regain those jobs. By your own argument, you should be voting Republican this November.” I meant my chart to be a sort of visual rhetorical trick to be played in the context of the Obama stimulus chart to show that the numbers can be spun in either direction.

This graph has been going around a good deal in the last week. (Source)

Basically, the light blue line is the unemployement rate the Obama administration predicted would happen if we didn’t pass the stimulus bill back in . The dark blue line is the unemployment rate the Obama administration predicted would happen if we did pass the stimulus bill. (Here’s the raw document.) And the red triangles are the actual unemployment rate as it has panned out. Not only are they worse than the Obama adminstration expected, they’re worse than what they expected even if we didn’t pass the stimulus bill.

I think it is fair to say that the stimulus bill has not been as stimulating as they told us it would be. Now, it could certainly be the case that the unemployment rate would be even higher than this if we hadn’t passed the stimulus bill, but that is about as non-falsifiable a statement as you can get.

(UPDATE: The author of this graph explains why he thinks there has been little effect … we’ve spent almost none of the stimulus money yet. I’m trying to figure out where he’s getting his data because I don’t see any infrastructure projects on there. I’m certain that there is infrastructure spending going on right now because there is a stimulus project not 3 miles from my house causing daily traffic jams.

I don’t really feel like dogpiling on the adminstration on this particular issue, so I want to hit a broader topic here… the administration’s use of numbers. This graph tells us some simple things that are scary and a complex thing that is scarier.

The simple thing it tells us is that the Obama administration was completely unable to predict the economic conditions four months into the future. They thought we would be at about 8.0% unemployment if the stimulus bill passed and at 8.5% unemployment if we sat on our hands.

As it turns out, we passed the stimulus bill and we’re at 8.9%. The easy lesson is that they didn’t get that one right. But, as Robert Strom Petersen said, “It’s tough making predictions, especially about the future.” And I probably couldn’t have done any better.

But no one is hanging the weight of hundreds of billions of dollars around my neck, which makes it more OK that I can’t project the future economic conditions. It seems fair to demand a slightly higher level of predictive accuracy from an administration that is using their predictions to push trillion dollar policies.

The complex thing that this graph tells us is that the Obama administration is comfortable using graphs that don’t really have a basis in reality in order to bolster support for their decisions. Graphs make us think that something is scientific and studied and therefore more reliable. But reliability is something that has to be earned. The team that put this graph together should be questioned on what they got wrong and what they would do next time to get it right.

Basically, the next time the president uses projected figures to push his policies, I would like to see someone ask the following question:

“Mr President, the last number predictions you threw at us turned out to be pretty far off the mark. What assurances do we have that these new numbers are accurate?”